The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
C-Rank Grade: B (Solid) - 54/100
External PR Merge Rate: 62%
Response Time: 5h
First Timer Success: 50%
huggingface/pytorch-image-models has a recorded first-timer success rate of 50.0%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in huggingface/pytorch-image-models respond to incoming external pull requests in approximately 4.7 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 53.8 places huggingface/pytorch-image-models in the B tier.
The external contributor pull request merge rate for huggingface/pytorch-image-models is 61.5%, based on public PR activity from non-core contributors.
huggingface/pytorch-image-models does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Active maintainer team in huggingface/pytorch-image-models welcoming community pull requests and bug fixes.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/huggingface/pytorch-image-models?utm_source=github&utm_medium=badge)
Historical health & responsiveness evolution
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
Calculating local time...
Calculating local time...
Detected: UTC
Maintainers are most responsive around 17:00 UTC (17:00 UTC in your timezone). Recommended submission window is Tuesday - Thursday from 15:00 to 19:00 UTC (15:00 - 19:00 UTC local).
Limited recent maintainer review activity recorded for this repository. Prediction based on heuristic baseline.
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~4 hours (77% approval). Large PRs (>500 lines) take ~22 hours (28% approval). Keep your diff compact for rapid review.
Enter your branch size and test coverage below to forecast review turnaround and get 1-click git splitting commands.
Alternative open-source projects with active maintainers in Python.
Trail of Bits Claude Code skills for security research, vulnerability detection, and audit workflows
Collection to install and configure Keycloak or Red Hat Single Sign-On / Red Hat Build of Keycloak
Checkpoint-engine is a simple middleware to update model weights in LLM inference engines
No cached good first issues currently tracked for huggingface/pytorch-image-models.
Rate what actually matters after opening a pull request here.
Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.
When evaluating whether to contribute to huggingface/pytorch-image-models, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of huggingface/pytorch-image-models acknowledge new external contributions in approximately 4 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 61.5% were successfully merged into the primary branch.
huggingface/pytorch-image-models has a recorded first-timer success rate of 50.0%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~4 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rankâ„¢ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 53.8 places huggingface/pytorch-image-models in the Solid tier.
The external pull request merge rate is 61.5%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
huggingface/pytorch-image-models does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for huggingface/pytorch-image-models are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.